353 lines
18 KiB
Python
353 lines
18 KiB
Python
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"""Beauty B2B AI assessment — cosmetics distribution lead qualification.
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Pre-scans scraped text for known brands, then sends a focused prompt to Gemini
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to evaluate fit as a B2B customer for a cosmetics distribution business.
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"""
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import asyncio
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import json
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import logging
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import os
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import re
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from typing import Optional
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import httpx
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from bs4 import BeautifulSoup
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logger = logging.getLogger(__name__)
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REPLICATE_TOKEN = os.getenv("REPLICATE_API_TOKEN", "r8_7I7Feai78f9PzMOs20y5GVFKiLkgUWP463vZO")
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REPLICATE_MODEL = "https://api.replicate.com/v1/models/google/gemini-3-pro/predictions"
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AI_CONCURRENCY = int(os.getenv("AI_CONCURRENCY", "3"))
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_ai_sem: Optional[asyncio.Semaphore] = None
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def _sem() -> asyncio.Semaphore:
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global _ai_sem
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if _ai_sem is None:
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_ai_sem = asyncio.Semaphore(AI_CONCURRENCY)
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return _ai_sem
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# ── Brand universe (market brands we can detect on client sites) ──────────────
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BEAUTY_BRANDS = [
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"4711","7days","7th Heaven","A-derma","Abercrombie & Fitch","Abril Et Nature",
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"Acqua Di Parma","Actinica","Adidas","Adolfo Dominguez","Aesop","Agatha Ruiz De La Prada",
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"Agave","Agua Lavanda","Ahava","Air-wick","Aire Sevilla","Al Haramain","Albal","Alcantara",
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"Alejandro Sanz","Alfaparf Milano","Algasiv","Alma Secret","Alpecin","Alqvimia","Alterna",
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"Alvarez Gomez","Alyssa Ashley","Ambi Pur","American Crew","Amichi","Ana María Lajusticia",
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"Angel Schlesser","Anian","Annayake","Anne Möller","Anso","Antonio Banderas","Apisérum",
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"Apivita","Aqc Fragrances","Aquilea","Aramis","Ardell","Arganour","Ariel","Armaf",
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"Armand Basi","Artdeco","Artero","As I Am","Aseptine","Atashi","Atrix","Ausonia","Aussie",
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"Australian Gold","Autan","Aveda","Avena Kinesia","Avène","Axe","Axovital","Azalea",
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"Azzaro","Babaria","Babyliss","Barbie","Bare Minerals","Barulab","Batiste","Beaver",
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"Beconfident","Belcils","Bella Aurora","Benefit","Benton","Benzacare","Beter","Biafin",
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"Bio Ionic","Bio-oil","Bioderma","Biolage","Biotherm","Biovène","Biretix","Bobbi Brown",
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"Bouclème","Bourjois","Bperfect Cosmetics","Britney Spears","Bumble & Bumble","Burberry",
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"Bvlgari","Byly","Byphasse","Cacharel","Calvin Klein","Camomila Intea","Cantu","Carefree",
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"Carmex","Carolina Herrera","Carrera","Carthusia","Catrice","Caudalie","Cerave","Cerruti",
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"Cetaphil","Chanel","Chanson D'Eau","Chloé","Chopard","Christina Aguilera","Christophe Robin",
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"Clarins","Clean & Clear","Clinique","Coach","Cocosolis","Colab","Colgate","Collistar",
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"Color Wow","Comfort Zone","Comodynes","Compeed","Cosrx","Creed","Creme Of Nature",
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"Cristalinas","Crossmen","Crusellas","Cryopharma","Cumlaude Lab","Cutex","Cygnetic",
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"Daffoil","Darphin","Davidoff","Declaré","Delfy","Delisea","Denenes","Dentiblanc",
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"Dermalogica","Desensin","Dexeryl","Diadermine","Diesel","Diet Esthetic","Dior","Diptyque",
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"Dodot","Dolce & Gabbana","Donna Karan","Dove","Dr. Hauschka","Dr.jart+","Dr. Organic",
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"Dr. Rimpler","Dr. Tree","Drasanvi","Drunk Elephant","Dsquared2","Ducray","Durex",
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"Elancyl","Elegant Touch","Elemis","Elie Saab","Elizabeth Arden","Elizabeth Taylor",
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"Emilio Pucci","Endocare","Eric Favre","Escada","Essence","Essie","Estée Lauder",
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"Etat Libre D'Orange","Eucerin","Eudermin","Evax","Eve Lom","Eylure","Fa","Fairy","Fanola",
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"Farmatint","Farmavita","Farouk","Figuière","Fisiocrem","Flor De Mayo","Fluocaril","Foreo",
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"Forté Pharma","Foxy","Francis Kurkdjian","Frederic Malle","Frosch","Garnier","Ghd",
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"Gillette","Giorgi Line","Givenchy","Glam Of Sweden","Goldwell","Gosh","Goutal","Gritti",
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"Gucci","Guerlain","Guess By Marciano","Gummy","Hair Rituel By Sisley","Hairgum","Halita",
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"Halloween","Hansaplast","Hask","Hawaiian Tropic","Head & Shoulders","Heliocare",
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"Heno De Pravia","Herbal Essences","Hermès","Hidracel","Hollister","Hugo Boss",
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"I.c.o.n.","Ibizaloe","Iceberg","Idc Institute","Iroha","Isabelle Lancray","Isdin",
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"Issey Miyake","It Cosmetics","Ivybears","Jacadi","Jean Paul Gaultier","Jil Sander",
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"Jimmy Choo","Jo Malone","John Frieda","Johnson's Baby","Joico","Joop","Jordan","Jowaé",
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"Juicy Couture","Juliette Has A Gun","Just For Men","Juvena","Kaloo","Karl Lagerfeld",
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"Karseell","Katai","Kate Spade","Kativa","Kenzo","Kerasilk","Kerastase","Kevin Murphy",
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"Kevyn Aucoin","Kilian","Klorane","L'Anza","L'Occitane","L'Oréal Paris",
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"L'Oréal Professionnel","La Cabine","La Mer","La Prairie","La Roche Posay","La Toja",
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"Laboratoires Filorga","Lacer","Lacoste","Lactacyd","Lactovit","Lalique","Lancaster",
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"Lanvin","Lattafa","Laura Biagiotti","Le Petit Marseillais","Legrain","Lierac","Listerine",
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"Living Proof","Loewe","Lola Cosmetics","Lolita Lempicka","Lussoni","Lutsine E45",
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"M2 Beauté","Mac","Macadamia","Mad Beauty","Maria Nila","Marlies Möller","Martiderm",
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"Martinelia","Marvis","Matrix","Maui","Mavala","Max Factor","Maybelline","Melvita",
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"Mermade","Michael Kors","Milk Shake","Mix & Shout","Mixa","Moroccanoil","Moschino",
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"Mustela","Nabeel","Nanobrow","Nanoil","Nanolash","Narciso Rodriguez","Nars","Natur Vital",
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"Natura Bissé","Natural Honey","Naturalium","Naturtint","Nenuco","Neogen","Neoretin",
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"Neostrata","Neutrogena","Nivea","Nûby","Nuggela & Sulé","Nyx Professional Make Up",
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"Ogx","Olaplex","Olay","Old Spice","Olivia Garden","Opi","Oral-b","Oraldine","Orofluido",
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"Orlane","Oscar De La Renta","Pacha","Paese","Palette","Paloma Picasso","Paltons",
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"Pantene","Paranix","Parfums Saphir","Parlux","Payot","Phyto","Picu Baby","Pilexil",
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"Piz Buin","Plantur 39","Platanomelón","Polaar","Police","Polident","Ponds","Poseidon",
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"Postquam","Proraso","Puig","Purito","Rabanne","Raid","Ralph Lauren","Rated Green",
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"Real Techniques","Redenhair","Redist","Redken","Reebok","Ref","Refectocil","Relec",
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"Remescar","Rene Furterer","Revlon","Revolution Hair Care","Revolution Make Up",
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"Revolution Pro","Rexaline","Rexona","Rilastil","Rimmel London","Roberto Cavalli","Roc",
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"Rochas","Roger & Gallet","Roja Parfums","Rosacure","S3","Sabon","Salerm","Sally Hansen",
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"Salvatore Ferragamo","Sanex","Sarah Jessica Parker","Saryna Key","Satisfyer","Scalpers",
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"Scholl","Schwarzkopf","Scottex","Sebamed","Sebastian Professionals","Seche Vite",
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"Sensai","Sensilis","Sensodyne","Serge Lutens","Serumkind","Sesderma","Seven Cosmetics",
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"Sexy Hair","Shiseido","Shu Uemura","Sisley","Skeyndor","Skin Generics","Sleek",
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"Snp","Soap & Glory","Sol De Janeiro","Solgar","Somatoline Cosmetic","Sophie La Girafe",
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"Soria Natural","Steinhart","Stendhal Paris","Sterimar","Strivectin","Suavinex",
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"Suavipiel","Svr Laboratoire Dermatologique","Syoss","System Professional","Tabac",
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"Taky","Talika","Tampax","Tangle Teezer","Tanit","Teaology","Tena Lady","The Body Shop",
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"The Ordinary","The Wet Brush","Thermacare","Tiffany & Co","Tigi","Timotei",
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"Tiziana Terenzi","Tod's","Tom Ford","Tommy Hilfiger","Topicrem","Torriden","Tot Herba",
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"Tous","Trendy Hair","Tresemme","Trussardi","Tulipán Negro","Urban Decay","Uriage",
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"Usu Cosmetics","Vagisil","Valmont","Valquer","Vanderbilt","Vaseline","Veet","Vichy",
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"Victor","Victoria's Secret","Victorio & Lucchino","Vital Proteins","Vivra",
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"Voltage Cosmetics","Volumax","Waterpik","Waterwipes","Wella","Weleda",
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"Williams","Woodwick","Xerjoff","Xls Medical","Yankee Candle","Yari","Yotuel",
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"Youth Lab","Zadig & Voltaire","Ziaja",
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]
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# Our distribution portfolio — the brands we sell to B2B clients
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OUR_BRANDS = [
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"AIMX","Al Haramain","Apivita","Armaf","Aveda","Bouclème","Clarena",
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"Curly Girl Movement","Cutrin","Davines","Dr. Hauschka","FanPalm","Farmavita",
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"Flora Curl","GAMMA+","GHD","GOSH","ICON","Image Skincare","Instituto Español",
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"Janeke","Kay Pro","Kerasilk","Kyo","Label M","Lierac","Living Proof","Londa",
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"M2 Beauté","Malibu C","Maria Nila","Medik8","Misslyn","Mustela","Nesti Dante",
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"Nuxe","Obagi","Osmo","Payot","Philip B","Philip Martins","Phyto","Piz Buin",
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"Ramon Monegal","Redken","REF","Saryna Key","Sesderma","Skala Brasil","Skin1004",
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"Strivectin","Swissdent","Topicrem","Uriage","Vita Liberata","Waterclouds",
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"Wella","Youngblood Cosmetics",
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]
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BEAUTY_CATEGORIES = [
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"Perfumes","Facial Cosmetics","Makeup","Hair Care","Health","Body Cosmetics",
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"Hygiene","Kids & Babies","Sun Care","Eyewear","Home","Nutrition","Erotic","Fashion",
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]
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# ── Brand detection (fast pre-scan, no AI) ─────────────────────────────────────
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def detect_brands_in_text(text: str) -> list[str]:
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"""Find which brands from the universe appear in the scraped page text."""
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tl = text.lower()
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return [b for b in BEAUTY_BRANDS if b.lower() in tl][:60]
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def get_dist_matches(detected: list[str]) -> list[str]:
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"""Return which detected brands are in our distribution portfolio."""
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dl = {b.lower() for b in detected}
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return [b for b in OUR_BRANDS if b.lower() in dl]
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# ── DuckDuckGo search (contact/company lookup) ────────────────────────────────
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async def _ddg_search(query: str) -> str:
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try:
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async with httpx.AsyncClient(
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timeout=10, follow_redirects=True,
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headers={"User-Agent": "Mozilla/5.0 (compatible; BeautyLeads/1.0)"},
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) as client:
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r = await client.get(
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"https://html.duckduckgo.com/html/",
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params={"q": query, "kl": "es-es"},
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)
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if r.status_code != 200:
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return ""
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soup = BeautifulSoup(r.text, "html.parser")
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parts = []
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for res in soup.select(".result")[:4]:
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title = res.select_one(".result__a")
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snip = res.select_one(".result__snippet")
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url = res.select_one(".result__url")
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if snip:
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t = title.get_text(strip=True) if title else ""
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u = url.get_text(strip=True) if url else ""
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parts.append(f"[{u}] {t} — {snip.get_text(strip=True)}")
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return "\n".join(parts)
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except Exception as e:
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logger.debug("DDG search failed: %s", e)
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return ""
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# ── Prompt builder ─────────────────────────────────────────────────────────────
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def _build_beauty_prompt(a: dict, detected_brands: list, dist_matches: list,
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search_results: str = "") -> str:
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contacts_block = []
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if a.get("emails"): contacts_block.append(f" Emails: {', '.join(a['emails'][:3])}")
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if a.get("phones"): contacts_block.append(f" Phones: {', '.join(a['phones'][:3])}")
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if a.get("social_links"): contacts_block.append(f" Social: {', '.join(a['social_links'][:4])}")
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contacts_str = "\n".join(contacts_block) or " Not found"
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snippet = (a.get("visible_text_snippet") or "")[:1200]
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title = a.get("page_title") or ""
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meta = a.get("meta_description") or ""
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country = a.get("ip_country") or "unknown"
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cms = a.get("cms") or "unknown"
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detected_str = ", ".join(detected_brands) if detected_brands else "none detected"
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dist_str = ", ".join(dist_matches) if dist_matches else "none"
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return f"""You are a senior B2B sales analyst for a cosmetics distribution company operating in Europe.
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Your task: evaluate whether this website is a viable B2B customer (retailer, multi-brand store,
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e-commerce, distributor or chain that buys beauty products wholesale) and generate an outreach plan.
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=== SITE DATA ===
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Domain: {a.get("domain")}
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Country (IP): {country}
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Title: {title}
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Meta desc: {meta}
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CMS: {cms}
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Contact info:
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{contacts_str}
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=== PAGE CONTENT SAMPLE ===
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{snippet}
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=== BRANDS ALREADY DETECTED ON SITE ===
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{detected_str}
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=== OUR PORTFOLIO BRANDS FOUND ON THEIR SITE ===
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(These brands we distribute — finding them means we're already in their market)
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{dist_str}
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=== WEB SEARCH RESULTS ===
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{(search_results or "No results.")[:500]}
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=== OUR DISTRIBUTION PORTFOLIO ===
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{', '.join(OUR_BRANDS)}
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=== BEAUTY CATEGORIES WE COVER ===
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{', '.join(BEAUTY_CATEGORIES)}
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=== ASSESSMENT RULES ===
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1. Determine if this is a B2B prospect: retailer, pharmacy, parafarmacia,
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perfumería, multi-brand beauty ecommerce, salon chain, supermarket beauty section,
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or beauty products distributor based in Europe.
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2. Identify which categories from our list they cover.
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3. From the page content (even if brands list is empty), identify any beauty brands mentioned.
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4. Match detected brands against our portfolio — this drives lead quality:
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- HOT: 3+ of our portfolio brands detected, OR a large EU retailer clearly in our niche
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- WARM: 1-2 portfolio brand matches, OR clear beauty retailer with good potential
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- COLD: beauty-adjacent but weak match, OR can't confirm they buy wholesale
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- NOT_RELEVANT: not a beauty business or not in Europe
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5. Write all human text (proposal, email) in Spanish.
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6. Keep JSON values concise (≤ 25 words each).
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Respond ONLY with valid JSON, no markdown, no text outside JSON:
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{{
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"is_relevant": true/false,
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"lead_quality": "HOT|WARM|COLD|NOT_RELEVANT",
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"lead_reasoning": "1-2 sentences why",
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"business_type": "retailer|ecommerce|distributor|pharmacy|salon_chain|other",
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"business_name": "name from title or domain",
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"country_fiscal": "2-letter ISO or full name",
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"countries_active": ["ES","FR"],
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"categories": ["Hair Care","Makeup"],
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"detected_brands": ["brand1","brand2"],
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"dist_matches": ["OurBrand1","OurBrand2"],
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"contact_email": "email or empty string",
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"contact_phone": "phone or empty string",
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"b2b_proposal": "1-2 sentence value proposition in Spanish referencing their categories and our matching brands",
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"outreach_subject": "short Spanish subject line referencing their business name",
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"outreach_email": "3-4 sentence ready-to-send email in Spanish. Mention their business, 1-2 specific brands from our portfolio that match their range, and a clear call to action (catálogo, muestra, llamada).",
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"revenue_estimate": "unknown",
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"outreach_notes": "brief context for sales rep"
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}}"""
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def _parse_beauty_output(raw: str) -> dict:
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text = re.sub(r"```(?:json)?", "", raw).strip().rstrip("`").strip()
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m = re.search(r"\{[\s\S]+\}", text)
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if m:
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candidate = m.group(0)
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try:
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return json.loads(candidate)
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except json.JSONDecodeError:
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depth_obj = candidate.count("{") - candidate.count("}")
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|
|
depth_arr = candidate.count("[") - candidate.count("]")
|
||
|
|
fixed = re.sub(r',\s*"[^"]*"?\s*:\s*[^,\}\]]*$', '', candidate)
|
||
|
|
fixed += "]" * max(0, depth_arr) + "}" * max(0, depth_obj)
|
||
|
|
try:
|
||
|
|
return json.loads(fixed)
|
||
|
|
except json.JSONDecodeError:
|
||
|
|
pass
|
||
|
|
logger.warning("Beauty AI parse failed, raw: %.300s", raw)
|
||
|
|
return {
|
||
|
|
"is_relevant": False,
|
||
|
|
"lead_quality": "COLD",
|
||
|
|
"business_name": "",
|
||
|
|
"contact_email": "",
|
||
|
|
"dist_matches": [],
|
||
|
|
"parse_error": True,
|
||
|
|
}
|
||
|
|
|
||
|
|
|
||
|
|
# ── Main entry point ───────────────────────────────────────────────────────────
|
||
|
|
|
||
|
|
async def assess_beauty_domain(analysis: dict) -> dict:
|
||
|
|
"""Full beauty B2B assessment: brand scan + AI evaluation."""
|
||
|
|
async with _sem():
|
||
|
|
domain = analysis.get("domain", "")
|
||
|
|
text = analysis.get("visible_text_snippet", "") or ""
|
||
|
|
html_raw = text # use snippet; brands already extracted from full page in site_analyzer
|
||
|
|
|
||
|
|
detected = detect_brands_in_text(text)
|
||
|
|
dist_match = get_dist_matches(detected)
|
||
|
|
|
||
|
|
# Also search for company context
|
||
|
|
title = analysis.get("page_title") or ""
|
||
|
|
biz_name = title.split("|")[0].split("-")[0].strip() or domain
|
||
|
|
search_results = await _ddg_search(f'"{biz_name}" {domain} beauty cosmetics wholesale contact')
|
||
|
|
logger.info("Beauty assess %s: %d brands detected, %d portfolio matches",
|
||
|
|
domain, len(detected), len(dist_match))
|
||
|
|
|
||
|
|
payload = {
|
||
|
|
"input": {
|
||
|
|
"prompt": _build_beauty_prompt(analysis, detected, dist_match, search_results),
|
||
|
|
"images": [], "videos": [],
|
||
|
|
"top_p": 0.9,
|
||
|
|
"temperature": 0.15,
|
||
|
|
"thinking_level": "low",
|
||
|
|
"max_output_tokens": 2000,
|
||
|
|
}
|
||
|
|
}
|
||
|
|
try:
|
||
|
|
async with httpx.AsyncClient(timeout=120) as client:
|
||
|
|
resp = await client.post(
|
||
|
|
REPLICATE_MODEL,
|
||
|
|
headers={
|
||
|
|
"Authorization": f"Bearer {REPLICATE_TOKEN}",
|
||
|
|
"Content-Type": "application/json",
|
||
|
|
"Prefer": "wait",
|
||
|
|
},
|
||
|
|
json=payload,
|
||
|
|
)
|
||
|
|
resp.raise_for_status()
|
||
|
|
data = resp.json()
|
||
|
|
|
||
|
|
output = data.get("output", "")
|
||
|
|
if isinstance(output, list):
|
||
|
|
output = "".join(output)
|
||
|
|
|
||
|
|
result = _parse_beauty_output(output)
|
||
|
|
# Merge pre-scan data that AI might miss
|
||
|
|
if not result.get("dist_matches") and dist_match:
|
||
|
|
result["dist_matches"] = dist_match
|
||
|
|
if not result.get("detected_brands") and detected:
|
||
|
|
result["detected_brands"] = detected
|
||
|
|
|
||
|
|
logger.info("Beauty AI %s → quality=%s, dist_matches=%s",
|
||
|
|
domain, result.get("lead_quality"), result.get("dist_matches"))
|
||
|
|
return result
|
||
|
|
|
||
|
|
except Exception as e:
|
||
|
|
logger.error("Beauty AI error %s: %s", domain, e)
|
||
|
|
return {
|
||
|
|
"error": str(e)[:300],
|
||
|
|
"is_relevant": False,
|
||
|
|
"lead_quality": "COLD",
|
||
|
|
"dist_matches": dist_match,
|
||
|
|
"detected_brands": detected,
|
||
|
|
"contact_email": "",
|
||
|
|
}
|